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Results for “Molecular Docking Simulation”

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PubMed2026

Mechanism exploration of divergent partial denitrification performance under tetracycline stress: Insights from functional gene, electron transport and molecular docking.

Nitrates and antibiotics like tetracycline (TC) coexist in wastewater and inhibit nitrite (NO₂--N) accumulation during partial denitrification (PD), restricting anammox coupling. A moving bed biofilm reactor (PD-MBBR) and a sequencing batch reactor (PD-SBR) were compared under TC stress (0-8 mg/L). The PD-MBBR proved more robust, sustaining a high nitrate transformation ratio (NTR) of 95.11% and ∼53% TC removal. Metagenomic sequencing, quantitative polymerase chain reaction (qPCR), and molecular docking revealed this tolerance stemmed from physical shielding and metabolic compensation. Carrier-attached growth promoted extracellular polymeric substances (EPS) overproduction, forming a dense barrier preventing TC from binding to key denitrifying enzymes. The biofilm maintained stable nitrate reductase (NAR) activity via high narG and napA gene abundances, while nitrite reductase (NIR) was inhibited, ensuring efficient NO₂--N accumulation. This was supported by hyperactivated electron transport chain components, with complex III relative abundance increasing 15.08% and peak enzymatic activity reaching 149.02%. While IntI1-mediated horizontal gene transfer fortified community defense, concentrated antibiotic resistance genes (ARGs) within the biofilm pose a secondary dissemination risk. Thus, PD-MBBR provides an efficient pretreatment strategy for anammox, though downstream ARGs management is warranted.

Denitrification↗

PubMed2026

Exploring the treatment of liver cancer with Gehua Hugan Gao based on bioinformatics, network pharmacology, and molecular docking.

Gehua Hugan Gao (GHHGG) is a traditional Chinese medicine paste that is chiefly used to treat liver cancer. However, the potential impact of GHHGG on liver cancer remains unclear. We explored how GHHGG treats liver cancer using bioinformatics, network pharmacology, and molecular docking. Network pharmacology included GHHGG active ingredients, predicted targets, predicted targets for liver cancer, and differential gene collection. A protein-protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and crucial targets were ranked according to their degree values. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of liver cancer targets were followed by survival, differential analysis, and molecular docking. Venn diagrams show 123 predicted GHHGG targets for the treatment of hepatocellular carcinoma (HCC). Enrichment analysis showed that GHHGG treats HCC through multiple targets and pathways. We also found that estrogen receptor 1, cytochrome P450 3A4, cyclin-dependent kinase 4, type IIA topoisomerase, aurora kinase A, and cyclin E1 targets were closely associated with HCC development through survival and differential analyses. Molecular docking confirmed GHHGG's strong affinity for liver cancer targets. This study helps us understand GHHGG ingredients and targets for liver cancer treatment. To a certain extent, the molecular mechanism of GHHGG in the treatment of liver cancer has been elucidated, thus providing a theoretical basis.

Molecular Docking Simulation↗

PubMed2025

Mechanism of action of curculigoside ameliorating osteoporosis: an analysis based on network pharmacology and experimental validation.

OBJECTIVE: This study aimed to predict and verify the mechanism of curculigoside in treating osteoporosis using network pharmacology, molecular docking technology, and micro-CT technology. METHODS: Herb databases were searched to identify and screen potential targets of curculigoside. The GeneCards platform was utilized to mine osteoporosis-related targets. Cytoscape 3.6.0 software was employed to construct a compound-target-disease network. A protein-protein interaction (PPI) network for curculigoside in osteoporosis treatment was established, and core targets were screened. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and GO biological process analyses were performed using the Metascape database. Finally, molecular docking and micro-CT were used to validate core targets relevant to osteoporosis. RESULTS: A total of 166 potential curculigoside targets and 4,313 osteoporosis-related targets were identified, with 91 common targets. Ten key targets, including matrix metalloproteinase (MMP)3, MMP9, interleukin (IL)-6, and caspase-3, were screened. KEGG pathway enrichment analysis indicated involvement in 10 pathways, such as the Rap1 signaling pathway and tumor necrosis factor (TNF) signaling pathway. Molecular docking results demonstrated strong binding affinity between curculigoside and the core targets. Micro-CT analysis revealed that curculigoside not only improved BMD, BV/TV, BS/BV, and Tb.Th but also reduced Tb.Sp in osteoporotic bone. CONCLUSIONS: Curculigoside is likely to treat osteoporosis through targets such as MMP3, MMP9, IL-6, and caspase-3, acting on signaling pathways including Rap1 and TNF. These results indicate that curculigoside exhibits multitarget and multipathway characteristics in osteoporosis treatment, providing a theoretical basis for further clinical investigation.

Osteoporosis↗

PubMed2025

Network pharmacology and molecular docking to explore the active compounds and mechanisms of Jerusalem artichoke for treating diabetes.

The effective components and mechanism of Jerusalem artichokes (JAs) in lowering blood glucose were studied through network pharmacology and molecular docking. The active compounds of Jerusalem artichoke were obtained by referring to the literature, and the active compounds were screened. The targets were predicted by the SwissTargetPrediction database, and the disease targets were screened using GeneCard, Disgenet, and OMIM databases. The protein-protein interaction (PPI) network diagram was constructed using the STRING database, and the intersection target was analyzed by gene ontology (GO) biological function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses using the David database. Finally, molecular docking was verified using AutoDockTools1.5.7 software. After screening, 412 gene targets, 476 disease targets, and 64 intersection targets were identified. The results of GO biological function analysis and KEGG pathway analysis showed that the technology was involved in multiple biological processes and regulatory pathways for hypoglycemia, such as the HIF-1, PI3K-Akt, and AMPK signaling pathways. Molecular docking results showed that Jasmonate, Liquiritigenin and Inulin of JAs had strong binding effects with PPARG and STAT3. JAs exert hypoglycemic effects through multi-component, multi-target and multi-pathway. In summary, this study investigated the hypoglycemic mechanism of JAs using network pharmacology and molecular interconnection technology, and concluded that JAs exert hypoglycemic effects through multiple components, targets, and pathways, which provides a theoretical basis for the study of JAs.

Molecular Docking Simulation↗

PubMed2025

Based on network pharmacology, molecular docking, and validation experiments to investigate the active components and mechanisms of action of Tibetan Medog County Citrus medica L.: In antioxidant activity.

BACKGROUND: The antioxidant potential of citrus plants is closely related to their geographical origin, making it crucial to evaluate the natural antioxidant properties of Citrus medica L. (C. medica) from Medog County, Tibet. METHODS: This study systematically investigates the antioxidant mechanisms of C. medica using network pharmacology, molecular docking, and experimental assays. RESULTS: The antioxidant activity experiments showed that C. medica exhibits good bioactivity, and the fruit has better antioxidant activity than the leaves. Network pharmacology revealed 11 active components of C. medica with 1547 antioxidant-related targets. Key targets include TP53, IL6, AKT1, STAT3, and TNF. Gene ontology (GO) analysis identified 1419 biological process entries, 147 cellular component entries, and 306 molecular function entries. Kyoto Encyclopedia of Genes and Genomes analysis identified 212 antioxidant-related signaling pathways. The GO and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the targets are involved in cancer pathways, protein binding, enzyme binding, lipid metabolism, and atherosclerosis. Molecular docking demonstrated that the 11 active components of Medog C. medica exhibit binding energies with core targets TP53, IL6, AKT1, STAT3, and TNF generally less than -5 kcal·mol-1, indicating good affinity. CONCLUSION: This study identifies the excellent antioxidant activity of C. medica from multiple aspects and elucidates its potential antioxidant mechanisms, providing a theoretical basis for the development and application of C. medica as an antioxidant functional additive.

Molecular Docking Simulation↗

PubMed2026

Discovery and characterization of multifunctional bioactive peptides from Alaska Pollock (Gadus chalcogrammus) milt: hybrid in silico, in vitro, and proteomic approaches.

The growing demand for multifunctional bioactive peptides has sparked interest in underutilized marine by-products as sustainable bioresources. This study explored Alaska Pollock (Gadus chalcogrammus) milt protein as a novel source of peptides with anti-inflammatory, anti-hypertensive, and anti-diabetic effects. Protein composition was analyzed via LC-MS, followed by in silico digestion and bioactivity prediction. Molecular docking identified peptides targeting DPP-IV, α-glucosidase, ACE, GLP-1 receptor, COX-2, MuRF1, and the 20S proteasome. Among the candidates, a promising peptide (CLPPH) was synthesized and validated in vitro, demonstrating inhibitory effects on nitric oxide production, DPP-IV, ACE, and α-glucosidase. These results highlight CLPPH's potential as a multifunctional bioactive peptide and support the valorization of Alaska Pollock milt as a sustainable source for functional foods and nutraceutical applications.

Animals↗

PubMed2026

Inhibitory mechanism of anthocyanin B-ring substituents on advanced glycation end-product formation through bovine serum albumin binding: Insights from multispectral, molecular docking and proteomics approaches.

This study demonstrated that the inhibitory effect of anthocyanins on AGEs formation is highly dependent on the substitution pattern of the B-ring. Among the four anthocyanins, delphinidin-3-O-glucoside (D3G) exhibited the most potent antiglycation activity across BSA-fructose, MGO, and GO models with half-maximal inhibitory concentration (IC50) of 30.77, 200.29 and 269.97 μM. This superior performance was attributed to the presence of three hydroxyl groups on the B-ring, which facilitates a high-affinity, spontaneous binding interaction with BSA primarily through hydrophobic forces and hydrogen bonding. Spectroscopic and computational analyses revealed that D3G effectively stabilizes the protein scaffold, specifically recovering α-helix content and shielding critical subdomains (IB, IIA, and IIIA). Proteomics data are consistent with a protective binding mechanism, suggesting that D3G reduces the accessibility of key lysine and arginine residues to glycation-induced modifications. These findings provide a structural basis for developing D3G-rich extracts as targeted, structure-based functional ingredients to mitigate glycation-associated food quality degradation and related health issues.

Anthocyanins↗

PubMed2025

Molecular mechanism of HaiZao-YuHu decoction in breast cancer treatment via network pharmacology and molecular docking: Computational pharmacology.

BACKGROUND: The molecular biological mechanisms of HaiZao-YuHu decoction were investigated using network pharmacology and molecular docking. METHODS: TCMSP database was used to collect the active ingredients and action targets of HaiZao-YuHu decoction, through the OMIM, PharmGkb, GeneCards, TDD, and DurgBank database query targets for breast cancer. Then, using the intersecting targets, the protein-protein interaction network of HaiZao-YuHu decoction was constructed using the STRING website. Network topology analysis was performed using Cytoscape 3.9.0 to identify the core targets. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed with the R package. The Autodock software was used for molecular docking. RESULTS: Thirty-four active ingredients, 219 intersection targets and 4 key targets were obtained. gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis get 2152 biological processes and 186 pathways. Molecular docking showed that the 4 core targets could combine well with the 5 main active components. CONCLUSION: HaiZao-YuHu decoction can play a role in the treatment of breast cancer through multi-targets, multi-components, and multi-pathways.

Molecular Docking Simulation↗

PubMed2025

Investigating the molecular mechanism of Yangxin decoction in treating major depressive disorder using network pharmacology and molecular docking technology approaches.

Yangxin decoction has been used to treat major depressive disorder (MDD). This study aims to identify the active components and potential mechanisms of Yangxin decoction in treating MDD using network pharmacology and molecular docking technology. The active components and targets of Yangxin decoction were screened, and MDD-related targets were predicted. Networks of "herbal medicine-active components-potential targets" and protein-protein interaction were constructed. Core components and core targets were identified through network topology analysis. Gene ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on candidate genes. Molecular docking was conducted using AutoDock software (Olson Laboratory of the Scripps Research Institute, San Diego) to explore the interactions between core targets and active components, and the results were visualized using PyMOL (DeLano Scientific LLC, South San Francisco). A total of 433 active components and 392 targets of Yangxin decoction were identified, along with 11,796 MDD-related targets. There were 680 overlapping targets between Yangxin decoction and MDD, associated with 104 active components. Core targets identified through network topology analysis and molecular docking included serine/threonine kinase 1 (AKT1), tumor necrosis factor, interleukin-6, tumor protein P53, and proto-oncogene tyrosine-protein kinase Src. Gene ontology enrichment analysis revealed 1606 biological processes, 191 cellular components, and 373 molecular functions. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified 212 signaling pathways, with significant enrichment in caffeine metabolism, bladder cancer, advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications, and vascular endothelial growth factor signaling pathway. Molecular docking results showed strong binding energy between core active components and core targets. Yangxin decoction exhibits multi-component, multi-pathway, and multi-target therapeutic characteristics. It primarily regulates targets such as AKT1, tumor necrosis factor, interleukin-6, tumor protein P53, and proto-oncogene tyrosine-protein kinase Src through advanced glycation end products-receptor for advanced glycation end products, vascular endothelial growth factor, and ErbB signaling pathways, exerting anti-inflammatory, immune-regulating, and oxidative stress-inhibiting effects to alleviate MDD.

Molecular Docking Simulation↗

PubMed2003

Molecular dynamics simulations of lignin peroxidase in solution.

The dynamical and structural properties of lignin peroxidase and its Trp171Ala mutant have been investigated in aqueous solution using molecular dynamics (MD) simulations. In both cases, the enzyme retained its overall backbone structure and all its noncovalent interactions in the course of the MD simulations. Very interestingly, the analysis of the MD trajectories showed the presence of large fluctuations in correspondence of the residues forming the heme access channel; these movements enlarge the opening and facilitate the access of substrates to the enzyme active site. Moreover, steered molecular dynamics docking simulations have shown that lignin peroxidase natural substrate (veratryl alcohol) can easily approach the heme edge through the access channel.

Benzyl Alcohols↗

PubMed2026

Binding analysis of the response regulator NarL protein to the promoter of the O6-methylguanine-DNA methyltransferase (ogt) gene in Salmonella Typhimurium.

BACKGROUND: Salmonella Typhimurium (STM) is a gram-negative bacterium that causes severe gastrointestinal disorders in both animals and humans. The regulation of DNA repair genes is critical for maintaining genomic stability of the bacteria. O6-methylguanine DNA methyltransferase (Ogt), plays a vital role in repairing alkylated DNA in STM; however, the transcriptional regulation of ogt gene remains poorly characterized. Furthermore, NarL is a transcriptional regulator, involved in the pathogenesis of STM under anaerobic condition. Therefore, this study investigated the interaction between NarL protein and the promoter region of the ogt gene. METHODS: In this study, narl gene was cloned in pET32a vector and NarL protein was expressed in Escherichia coli BL21 (DE3). Subsequently, the ogt gene promoter (pogt) was selected, amplified, cloned and its activity was evaluated. Electrophoretic mobility shift assay (EMSA), isothermal titration calorimetry (ITC), molecular docking were employed to elucidate the interaction between NarL protein and ogt promoter. Furthermore, the regulatory role of NarL in ogt gene expression was validated in vivo using RT-qPCR and β-galactosidase assay. RESULTS: This study resulted that NarL protein interacts specifically with the ogt promoter, as confirmed by EMSA and ITC, with ΔG of - 9.42 kcal mol⁻¹. Furthermore, RT-qPCR and β-galactosidase assays demonstrated that deletion of narl significantly (P ≤ 0.01) decreased ogt transcript levels and promoter activity than wild Salmonella Typhimurium, whereas exogenous supplementation of recombinant NarL protein restored the expression. These findings suggest that NarL plays a potential regulatory role in ogt gene expression in response to environmental signals. CONCLUSION: These findings highlight an interaction between NarL protein and the promoter region of ogt gene in Salmonella Typhimurium, linking nitrogen metabolism with the DNA repair pathway in STM, which may contribute to the bacterial survival under nitrosative stress.

Salmonella typhimurium↗

PubMed2026

Resveratrol Attenuates Gemcitabine Resistance in Hepatocellular Carcinoma Cells by Inhibiting Thymidylate Synthase.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide. Gemcitabine (Gem) is a commonly used drug against HCC, but its efficacy is limited by the development of resistance. Resveratrol (Res), a natural polyphenol with antitumor activity, may reverse Gem resistance in HCC, although the mechanism remains unclear. METHODS: The effects of Res on the proliferation, apoptosis, cell cycle, and invasion of Hep3B and HuH-7 cells were assessed via cell counting kit-8 (CCK-8), clonogenic, flow cytometry, and Transwell assays, respectively. Potential Res targets were predicted by network pharmacology, and markers of HCC prognosis were identified from the cancer genome atlas (TCGA) data. The interaction between Res and thymidylate synthase (TYMS) was validated by molecular docking and dynamics simulation. A Gem-resistant HuH-7 cell line (HuH-7/GR) was established, and when these cells were treated with Res combined with Gem, the effect on Gem sensitivity was detected by CCK-8 assay, clonogenic assay, and flow cytometry. Finally, a subcutaneous nude mouse model of HCC was used to evaluate the in vivo effects of Res combined with Gem. RESULTS: Res inhibited HCC cell proliferation, induced apoptosis and G2/M arrest, and suppressed invasion in a concentration-dependent manner. Network pharmacology and TCGA analysis identified TYMS as an important target gene for Res. TYMS was highly expressed in HCC tissues and correlated with poor prognosis. Res treatment reduced TYMS expression, while molecular docking and simulation showed stable binding of Res to TYMS. TYMS levels were elevated in HuH-7/GR resistant cells. Res combined with Gem was found to reverse drug resistance, inhibit proliferation and colony formation, and induce apoptosis. The Res + Gem combination group showed the smallest tumor volume in the in vivo model. CONCLUSION: By attenuating Gem resistance through TYMS inhibition, Res holds promise as a clinically viable adjunct to Gem-based chemotherapy, offering a potential strategy to improve outcomes in HCC patients.

Resveratrol↗

PubMed2026

Gut microbiota-derived metabolites target C5AR1/KDM2A/HCAR3 axis in inflammatory bowel disease: a multi-machine learning algorithms and molecular docking study.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic recurrent disorder. Gut microbiota-derived metabolites regulate intestinal homeostasis, but their molecular mechanisms in IBD remain unclear. Current studies lack systematic "microbiota-metabolite-target" network mining with multi-method validation. This study integrates network pharmacology, three machine learning algorithms, and molecular docking to construct this regulatory network in IBD. METHODS: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using limma (p < 0.05, |log2FC| > 0.5). Weighted gene co-expression network analysis (WGCNA) with an optimal soft threshold of β = 7 was performed to identify key module genes. Candidate genes were obtained by intersecting DEGs, gut microbiota-associated genes from the gutMGene database, and WGCNA module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of candidate genes. Core genes were identified using three machine learning algorithms (LASSO, Boruta, and SVM-RFE), followed by protein-protein interaction (PPI) network analysis. Molecular docking was performed to assess the binding affinities between hub proteins and gut microbiota-derived metabolites. RESULTS: A total of 885 DEGs were identified between the IBD and control groups, including 463 upregulated and 422 downregulated genes. WGCNA identified 280 key module genes from the purple and yellow modules. The intersection of DEGs, gut microbiota-associated genes, and WGCNA module genes yielded 19 core candidate genes. PPI network analysis combined with three machine learning algorithms jointly identified C5AR1, KDM2A, and HCAR3 as core hub genes. ROC curve analysis demonstrated that all three hub genes achieved AUC values greater than 0.7 in both the training and validation sets, indicating excellent diagnostic performance for IBD. Enrichment analysis revealed significant associations with the TNF, NF-κB, and IL-17 signaling pathways. Molecular docking confirmed stable binding of C5AR1 with 1,3-Diphenylpropan-2-Ol (-7.87 ± 0.83 kcal·mol-¹) and HCAR3 with 3-Indolepropionic Acid (-6.35 ± 0.70 kcal·mol-¹), both below -5.0 kcal·mol-¹. CONCLUSION: This study first constructs a "gut microbiota-metabolite-hub gene" axis in IBD, providing a computational framework for microbiota-targeted precision therapy, and identifying C5AR1/KDM2A/HCAR3 as computationally predicted diagnostic biomarkers and 1,3-Diphenylpropan-2-Ol/3-Indolepropionic Acid as candidate intervention molecules that warrant further experimental validation.

Molecular Docking Simulation↗

PubMed2026

Integrated network pharmacology, molecular docking, and experimental validation to reveal the potential mechanism of Ginsenoside Rg1 on chronic obstructive pulmonary disease.

Ginsenoside Rg1 (GS Rg1), a natural flavonoid exhibiting anti-inflammatory and antioxidant properties, holds significant potential for treatment chronic obstructive pulmonary disease (COPD). Nevertheless, the precise mechanisms underlying its therapeutic effects remain to be fully elucidated. This study aimed to explore the role and potential mechanism of GS Rg1 in the treatment of COPD using network pharmacology, molecular docking, and experimental validation.Targets related to GS Rg1 and COPD were screened from public databases, and the potential common targets were then imported into the STRING database to construct a protein-protein interaction (PPI) network. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were performed to identify key signaling pathways. Molecular docking was employed to predict the binding interactions between GS Rg1 and core targets. A BEAS-2B cell model induced by lipopolysaccharide(LPS) and cigarette smoke extract(CSE) was used to explore the protective mechanisms of GS Rg1. Western blot analysis was conducted to validate the critical targets and pathways involved in the anti-COPD effects of GS Rg1. Network pharmacology analysis revealed 105 common targets between GS Rg1 and COPD. The EGFR/PI3K/AKT and EGFR/STAT3 signaling pathways were selected for further validation. GS Rg1 was demonstrated to effectively inhibit inflammation and mucus hypersecretion in vitro models of COPD. Western blot results showed that GS Rg1 treatment significantly downregulated the expression of proteins involved in the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathway, consistent with the network pharmacology findings. CSE/LPS exposure induces inflammation and oxidative stress in COPD by disrupting the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathways, and GS Rg1 significantly alleviates these effects, which may be partially through regulating the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathway.

Ginsenosides↗

PubMed2026

Computational prediction of a multi-epitope Human Metapneumovirus vaccine candidate through integrated reverse vaccinology and pan-genomic approaches.

Human metapneumovirus (HMPV) is a primary cause of global respiratory infections yet no approved vaccine currently exists. This study computationally predicts a multi-epitope vaccine candidate using a diverse dataset of 65 HMPV sequences spanning five continents. Following the screening of lead proteins for antigenicity and virulence, fifteen highly conserved MHC-I, MHC-II and B-cell epitopes were prioritized. These were integrated with a putative L7/L12 adjuvant using optimized AAY, GPGPG, and KK linkers to design three constructs (HMPV_V1-V3). Structural validation identified HMPV-V2 as the lead candidate that exhibits a Z-score of-5.24 and 87.7% of residues in favored Ramachandran regions indicating excellent stereochemical quality and structural stability. In silico docking indicated a strong predicted binding affinity between HMPV-V2 and the TLR4 receptor (energy: -969.2). Immune simulations predicted a robust adaptive response characterized by high IgG1 titers, memory B-cell maturation, and a Th1-dominant cytokine profile. Furthermore, molecular dynamics simulations suggested exceptional structural integrity for HMPV-V2, maintaining a low RMSD of 8.213 and RMSF of 0.737 throughout the simulation. Optimized in silico cloning into the pET28a (+) vector indicated a high potential for protein expression in E. coli systems. While these findings provide a theoretically grounded blueprint for vaccine development, this study is entirely computational and lacks experimental validation. Further in vitro and in vivo testing is required to confirm the actual safety and immunogenicity of the proposed candidate.

Metapneumovirus↗

PubMed2026

Multitargeted comparative evaluation suggests 2-Aoeobenoxmide shows favourable in silico binding compared to Tucatinib against ERα, HER2, AKT1, EGFR, and PIK3CA in breast cancer.

Breast cancer is a leading cause of cancer-related morbidity and mortality globally, with the WHO reporting approximately 2.3 million new cases and 685,000 deaths annually. Drug resistance in breast cancer complicates treatment, with mutations in critical proteins contributing to therapy failure. Key oncogenic proteins involved in breast cancer progression-namely ERα (a ligand-activated nuclear receptor; PDB: 1A52) and the kinase domains of HER2 (PDB ID: 3PP0), AKT1 (PDB ID: 4EJN), EGFR (PDB ID: 4I23) and PIK3CA (PDB ID: 7R9V)-are pivotal in tumour progression and resistance mechanisms. Targeting these proteins using multitargeted therapeutic strategies may overcome resistance by disrupting key signalling pathways involved in cell proliferation, survival, and metastasis. Such combinatorial approaches promise to improve treatment efficacy and patient outcomes in cases of resistant breast cancer. In this study, we performed multitarget docking on prepared and validated protein structures against the ZINC natural compound library using HTVS, SP, and XP, with pose validation using MM-GBSA. We identified 2-Aoeobenoxmide (2-[1-(2-amino-2-oxo-ethoxy)-6-oxo-benzo[c]chromen-3-yl]oxyacetamide, ZINC134008) with docking and MM-GBSA scores ranging from -8.162 to -10.327 kcal/mol and from -47.18 to -57.62 kcal/mol, respectively, and compared the results with the FDA-approved drug Tucatinib, which exhibited lower binding affinity scores. We further evaluated pharmacokinetic properties using QikProp and electronic properties using DFT (Jaguar) and compared the descriptors of 2-Aoeobenoxmide with those of Tucatinib and with accepted reference ranges. We also performed the WaterMap for 5 nanoseconds (ns), computed various energies, interactions and hydration sites, and the comparison suggests that 2-Aoeobenoxmide shows more favourable hydration-site displacement and binding interactions than Tucatinib. Additionally, a 100 ns MD Simulation has resulted in far less deviation, fluctuations, and intermolecular interactions than Tucatinib, suggesting stable protein-ligand interactions, while the binding free energy and total complex energy computed across 0-1000 frames of the MD trajectories indicate that 2-Aoeobenoxmide is a promising in silico candidate. Importantly, because the entire study is computational, the findings should be interpreted as in silico hypotheses, and experimental validation through in vitro and in vivo assays is warranted before any clinical translation is considered.

Humans↗

PubMed2005

Structure of Thermus thermophilus type 2 isopentenyl diphosphate isomerase inferred from crystallography and molecular dynamics.

Crystal structures of Thermus thermophilus and Bacillus subtilis type 2 IPP isomerases were combined to generate an almost complete model of the FMN-bound structure of the enzyme. In contrast to previous studies, positions of flexible loops were obtained and carefully analyzed by molecular dynamics. Docking simulations find a unique putative binding site for the IPP substrate.

Carbon-Carbon Double Bond Isomerases↗

PubMed2004

Localization of the antimitotic peptide and depsipeptide binding site on beta-tubulin.

Several naturally occurring peptides and depsipeptides which include the cryptophycins, dolastatin 10, hemiasterlin, and phomopsin A have been found to be potent antimitotic agents, causing cell death at picomolar or low nanomolar concentrations. These compounds inhibit microtubule growth, modulate the dynamics of microtubules, and induce the self-association of tubulin dimers into single-walled rings and spirals. These peptides exhibit mutual competitive inhibition in binding to beta-tubulin, while noncompetitively inhibiting the binding of vinblastine and vincristine to beta-tubulin. Despite the abundance of biochemical information, the details of their molecular interactions with tubulin are not known. In this study, using a combination of molecular dynamics simulations and molecular docking studies, a common binding site for cryptophycin 1, cryptophycin 52, dolastatin 10, hemiasterlin, and phomopsin A on beta-tubulin has been identified. Application of these same methods to alpha-tubulin indicated no interaction between alpha-tubulin and any of the peptides. On the basis of the docking results, a model for the mechanism of microtubule disruption and formation of aberrant nonmicrotubule structures is proposed. Both the active site and mechanism of microtubule depolymerization predictions are in good agreement with experimental findings.

Amino Acid Sequence↗